A recommender system is a system that gives the suggestions to the users about the items that might be of their interest. In this era of information overload, the library system offers a wide verity of books to its users. The library users face a lot of problems in getting and finding favorite books
Eminent content reading recommend-er system
A recommender system is a system that gives the suggestions to the users about the items that might be of their interest. In this era of information overload, the library system offers a wide verity of books to its users. The library users face a lot of problems in getting and finding favorite books from a large collection of available content in the library system. Efficiency and effectiveness of library recommender system is a significant issue which could enhance student’s performance. The library users need help in finding books that are in accordance with their interests in a quick way.
Therefore, the main concern of this study is, how to provide recommendations to library users efficiently and speedily.
The main focus of this study is to provide recommendations to library users efficiently and speedily. The following objectives have been set out to accomplish the research’s goal:
• To gain deeper knowledge about what recommender systems are, how they work and what influence they have on online customers and market.
• The primary objective of our research is to provide efficient recommendations to library users
• To implement an effective and efficient approach to the library system so that it could recommend items according to user needs.
Considering the research objectives, we have presented a new concept in library recommendation systems that provide efficient and quick recommendations to its users through the use of tokenization and basic TF-IDF technique. The proposed approach has been implemented on a web-based library management system and results have been compared with the basic searching technique, to evaluate the efficiency of the proposed solution.
With respect to implementation of tokenization, we quantified different metrics including execution time and book number. By achieving efficient performance while recommending, this proposed solution outperformed to other existing searching techniques. The suggested approach could be considered promising for achieving the best performance in library recommender systems.
The achieved results were better than the existing state-of-the-art technologies.
• Library recommender system provide efficient recommendations to users. These offer recommender system to reduce information overload problem in libraries.
• LRS provide books to users that are exactly match to their query and also according to high rating books that are rated by the previous users.
• By this, users will be able to retrieve required items efficiently and effectively in less time.
The final deliverable will be in the form of research i.e Reaserch papers and the acheived results.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Computer System | Equipment | 1 | 60000 | 60000 |
| Stationary and printing | Miscellaneous | 1 | 10000 | 10000 |
| Publication Fee | Equipment | 1 | 10000 | 10000 |
| Total in (Rs) | 80000 |
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